EGU22-3492
https://doi.org/10.5194/egusphere-egu22-3492
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

MeteoInfo: An open-source GIS, scientific computation and visualization platform

Yaqiang Wang
Yaqiang Wang
  • Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, China (yqwang@cma.gov.cn)

Earth science data usually have distinct three-dimensional spatial characteristics, in which the state of the atmosphere changes rapidly, the time dimension is also very important, and the variables that describe various physical and chemical states together constitute the earth science cube. GIS, scientific computation and visualization tools are important to find and extract patterns and scientific views behind the data. MeteoInfo open-source software was developed as an integrated framework both for GIS application and scientific computation environment with two applications for end users: MeteoInfoMap and MeteoInfoLab. MeteoInfoMap makes it quick and easy to explore many kinds of geoscience data in the form of GIS layers, and includes spatial data editing, projection and analysis functions. MeteoInfoLab includes multidimensional array calculations, scientific calculations such as linear algebra, and 2D/3D plotting functions, which are suitable for completing the tasks of geoscience data analysis and visualization. The software was developed using Java and Jython, which makes it has good cross-platform capabilities and can run in operating systems such as Windows, Linux/Unix, and Mac OS with Java supporting.

The functions can be conveniently extended through development of plugin for MeteoInfoMap and toolbox for MeteoInfoLab. For example, TrajStat plugin was developed for air trajectory analysis and air pollution source identification, which has been widely used in air pollution transport pathway and spatial sources studies. Several MeteoInfoLab toolbox were also developed for model evaluation (IMEP), air pollution emission data processing (EMIPS) and machine learning (MIML). MeteoInfoLab has similar functions with Python scientific packages such as numpy, pandas and matplotlib, also Jython is just Python in Java. So, the users can learn MeteoInfoLab easily when they have Python experience, vice versa. 3D visualization functions are more powerful in MeteoInfoLab due to the usage of opengl acceleration. Also, 3D earth coordinate is supported to plot geoscience data on virtual earth.

References:

Wang, Y.Q., 2014. MeteoInfo: GIS software for meteorological data visualization and analysis. Meteorological Applications, 21: 360-368.

Wang, Y.Q., 2019. An Open Source Software Suite for Multi-Dimensional Meteorological Data Computation and Visualisation. Journal of Open Research Software, 7(1), p.21. DOI: http://doi.org/10.5334/jors.267

Wang, Y.Q., Zhang, X.Y. and Draxler, R., 2009. TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environmental Modelling & Software, 24: 938-939

How to cite: Wang, Y.: MeteoInfo: An open-source GIS, scientific computation and visualization platform, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3492, https://doi.org/10.5194/egusphere-egu22-3492, 2022.